Crop wild relative populations of Beta vulgaris as source for genome-wide association mapping of complex traits.

Wild beet populations can be used for the detection of minor genes underlying quantitative traits Wild beet populations as valuable source for new genetic variation have so far not been used to detect minor genes underlying quantitative traits, such as drought tolerance or yield. These traits cannot be assessed in wild beets per se but require the development of a beet for phenotypic evaluation. Hence, crossing to elite genome is necessary. Our objective was to determine how QTL detection is affected by (1) the properties of the wild beet population, (2) the quantitative trait architecture, and (3) the structure of the mapping populations. Based on genotypic data of three wild beet populations, nine crossing designs to construct mapping populations were simulated and evaluated for their power to detect minor QTL and their false detection rate. Mapping populations containing 50% wild beet genome have the highest power in this study and can detect even QTL with allele frequencies of < 1% with reasonable power. However, to allow for reasonable phenotyping within field trials at least 75% elite genome in the mapping population is needed. We conclude that crossing designs based on elite x wild beet F1s are most suitable for genome-wide association mapping of complex traits in wild beet populations.